Summary
There is a significant amount of scientific research that shows that intelligent tutoring systems (ITS) can help students learn better than through other forms of instruction and software. These systems give frequent, fine-grained guidance when students practice solving complex problems. ITS have proven to be useful in many domains, for example, STEM, business, and language learning. The primary goal of this project is to investigate whether and how Large Language Models (LLMs) can help instructors author ITS effectively and efficiently – a process that needs to be executed each time an ITS is
